PROJECT SUMMARY-The project will investigate differences in the psychological, physical and social health of U.S. metropolitan statistical areas. It is based on the assumption that there are meaningful differences in the average psychological and physical health of geographically- defined areas; and that understanding these sociological-level differences may enable us to better predict and understand psychological and physical health at the individual level. The project will focus on two main sources of data. First, it will replicate (to examine changes) and extend the PI's earlier field experiments in 36 cities across the United States concerning two issues: the general pace of life during main business hours and the willingness to help strangers in distress. The main concerns of this portion of the proposed project will be to identify city-level differences in the pace of life, to track differences over the past decade, to identify community-level variables which predict these differences, and to identify the consequences of these differences for the psychological, physical and social health of these communities. The second series of questions focuses on the more general issue of city- level health differences. This portion of the project focuses on newly available data from the Center for Disease Control=s (CDC) annual Behavioral Risk Factor Surveillance Survey (BRFSS). The BRFSS has targeted the physical and psychological health of more than 100,000 individuals across the U.S. each year since 1993. This is the first national health survey which tests a sufficient number of respondents to allow generations at the level of metropolitan areas. The proposed study will be the first comprehensive research project to use the BRFSS data set to measure the theoretical model which describes the relationship of indicators of the physical/psychological health of communities to other demographic, environmental, economic, social and psychological characteristics (such as the pace of life and pro-social behavior) of these communities. This model will be used to derived observed and expected values on the BRFSS in order to see it is possible to predict individual responses to the BRFSS from demographic, environmental, economic and social indicator information.